Published November 11, 2018 | Version 1.0
Poster Open

Operationalizing and evaluating the FAIRness concept for a good quality of data sharing in Research: the RDA-SHARC-IG (SHAring Rewards and Credit Interest Group

  • 1. IMBE - Institut méditerranéen de biodiversité et d'écologie marine et continentale
  • 2. UPS - Université Toulouse III - Paul Sabatier
  • 3. ICGM ICMMM - Institut Charles Gerhardt Montpellier - Institut de Chimie Moléculaire et des Matériaux de Montpellier
  • 4. Department of Clinical Genetics/EMGO Institute for Health and Care research
  • 5. IRD-UMS PatriNat-GBIF
  • 6. University of Oxford
  • 7. UGENT - Ghent University
  • 8. Department of Biology - McGill University
  • 9. Istituto Superiore di Sanita
  • 10. The University of Sydney
  • 11. Independant
  • 12. FRB - Fondation pour la recherche sur la Biodiversité
  • 13. BONSAI - Bioinformatics and Sequence Analysis
  • 14. Biothèque Wallonia-Bruxelles
  • 15. University of Lincoln
  • 16. Murphy Mitchell Consulting Ltd
  • 17. P3G
  • 18. I2MC - Institut des Maladies Métaboliques et Cardiovasculaires
  • 19. CNR-IREA Milan

Description

The RDA-SHARC (SHAring Reward & Credit) interest group is an interdisciplinary volunteer member-based group set up as part of RDA (Research Data Alliance) to unpack and improve crediting and rewarding mechanisms in the sharing process throughout the data life cycle. Background and objectives of this group are reported here. Notably, one of the objectives is to promote the inclusion of data sharing activities in the research (& researchers) assessment scheme at national and European levels. To this aim, the RDA-SHARC-IG is developing two assessment grids using criteria to establish if data are compliant to the F.A.I.R principles (findable /accessible / interoperable / reusable) based on previous works on FAIR data management (Reymonet et al., 2018; Wilkinson et al., 2018; and E.U.Guidelines*): 1/ The self-assessment grid to be used by a scientist as a ‘checklist’ to identify her/his own activities and to pinpoint the hurdles that hinder efficient sharing and reuse of his/her data by all potential users. 2/ The two-level grid (quick/extensive) to be used by the evaluator to assess the quality of the researcher/scientist sharing practice, over a given period, taking into account the means & support available over that period. Assessment criteria are classified according their importance with regards to FAIRness (essential / recommended / desirable) meanwhile good practices are recommended for critical steps. To implement a highly fair assessment of the sharing process, appropriate criteria must be selected in order to design optimal generic assessment grids. This process requires participation, time and input from volunteer scientists data producers/users from various fields.

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